Predator–prey interactions are probably one of the key mechanisms for explaining the evolution of organisms in their ecosystems. Scientific fields relevant to understanding the mechanisms of these interactions are as diverse as evolutionary biology, behavioral ecology, ecomorphology, molecular biology, phylogeny, neurosciences, physiology, biomechanics, and robotics. The difficulty in understanding these mechanisms lies therefore (1) in the multi- and interdisciplinary nature of this issue, and (2) in keeping up with very rapid developments in various scientific fields. This Special Issue provides an interdisciplinary approach to predator–prey interactions to identify how phenotypic traits of both types of organisms interact and how each can act as a selective pressure on the evolution of a population of organisms at the different levels of the trophic chain. Moreover, we show that confronting bodies of knowledge that a priori appear as remote as those of robotics and experimental biology or ecology may seem difficult but can provide reciprocal understanding.

In this article I briefly discuss the role that artificial (robotic) models can play in the study of competing co-evolutionary dynamics, the main results obtained in the research works addressing the evolution of predator and prey robots, and the implications of these studies for robotics. In particular I discuss the factors that cause the convergence toward a cyclical dynamic and the factors that enable prolonged innovation phases eventually leading to open-ended processes.

Food acquisition mode in lizards (i.e., ambush vs. widely searching) has been intensely scrutinized for the past decade to identify correlations between food acquisition mode, diet, sprint speed, and other aspects of phenotypic diversity. To begin to understand these correlations, we studied foraging mode variation in natural foraging behavior and attack speed in three ambush predators and two widely foraging species in the field. Sequential analyses revealed considerable variation in the temporal structure of behavioral repertoires associated with acquiring food. Ambush and wide-foraging species use unique combinations of behaviors prior to prey attack with differences among and between food acquisition modes. Attack speeds were well below maximum sprint speed for these species. Thus, the widely demonstrated correlation between food acquisition mode and sprint speed is not related to prey capture per se. The striking variation in prey capture repertoires in these model ambush and wide foragers shows that we have a long way to go before we will understand the ecological relevance of many performance and phenotypic traits that are related to foraging mode in lizards.

Mammals possess a wide range of behavioral and morphological adaptations to help detect, assess, deter, and escape from predators, including weaponry that is useful in antipredator defense. While some weapons have evolved in response to natural selection for defense against predators, others may have evolved to serve some other primary function (e.g., intraspecific aggression) but still have defensive uses. In this comprehensive review of extreme morphological weaponry in mammals, I explore specific hypotheses regarding the ecological, morphological, and behavioral correlates of different types of weaponry in order to explain why some taxa have evolved elaborate weapons while others have not. I provide evidence demonstrating that several types of defensive weaponry (e.g., spines, quills, armor, noxious anal secretions) have evolved directly in response to significantly increased potential predation risk. Further, other structures that evolved primarily for intrasexual competition (e.g., cranial weaponry, tusks) or foraging (e.g., enlarged claws) but have additional defensive benefits are more likely to be found in larger species that are able to defend themselves in physical combat. Further comprehensive phylogenetic and comparative studies are needed to confirm the proposed hypotheses regarding selection, ecology, and function.

Schooling behavior in fish has been recognized to confer antipredator advantages. However, the mechanisms that lead to various patterns of escape maneuvers in fish schools are largely unknown. Here, we investigated the effect of startle stimulus characteristics (distance and orientation) on the escape maneuvers of schools of a highly gregarious fish species, the Atlantic herring Clupea harengus. We quantified information transfer of the onset of startle responses by analyzing the speed of the waves of their propagation (U_w = 6.7 ± 1.6 m/s; mean ± SD). U_w was found to be positively correlated with the number of early responders (i.e., individuals reacting with a latency <50 ms). In addition, we identified the rules determining two different evading maneuvers: highly aligned maneuvers (i.e., all individuals oriented in a relatively uniform direction) and "split" maneuvers (i.e., individuals escaping with low directional uniformity). The pattern of escape maneuvers was dependent on stimulus direction (α_s). Lateral stimulation (30° < α_s < 120°) elicits highly aligned maneuvers away from the stimulus, while frontal stimulations (α_s < 30°) causes split maneuvers, which are followed by realignment about 1 s after stimulation. These simple rules suggest that certain stimulus characteristics are important factors determining the variability of antipredator maneuvers observable in schooling fish.

Copepods are important grazers on microplankton in marine food webs and are, in turn, preyed upon by a wide range of predators with diverse feeding adaptations. Although copepods have evolved numerous adaptations to help them avoid predation, their escape behavior sets them apart from many other planktonic organisms. Mechanoreception is widely used by copepods to detect hydrodynamic disturbances created by approaching predators. When these disturbances are detected, copepods respond quickly with escape jumps that can accelerate them from a stationary position to speeds of over 600 body lengths per second within a few milliseconds. Myelinated nerves may improve the escape behavior of some copepods through faster conduction of nerve impulses. The differences in response latencies between myelinate and amyelinate copepod species are greatest in larger copepod species, where nerve signals must be conducted over longer distances. Environmental variability such as turbulence may affect the ability of both prey to detect predators and predators to capture their planktonic prey. Small amounts of turbulence favor the predator, while too much turbulence reduces predation. Understanding the sensory physiology of copepods and their behavioral adaptations for avoiding predation will increase knowledge of the factors affecting the structure and function of marine pelagic food webs.

Tetrapods with highly different morphologies occupy ecological niches of the canopy making them ideal for testing the evolution of structures and performances under similar environmental selective pressures. We compared leap up strategies between two distantly related amniote species, Anolis carolinensis (Squamate) and Microcebus murinus (Lemuriform) known to use leaping as their major locomotor mode for predator avoidance. Our comparative analysis and model show that leaping strategies (flat jump trajectory in horizontal leaps, use of forelimbs in landing) are similar in both species. The most striking divergence concerns only the temporal joint sequence accommodation to leaping height, although an identical proximal-to-distal sequence is observed when both taxa leap to maximal height. We suggest a convergent exaptation of leaping biomechanics among arboreal amniotes, which reflects similar biomechanical constraints and evolutionary pressures in these animals.

This article models the learning process of a population of randomly rematched tabula rasa neural network agents playing randomly generated 3 x 3 normal form games of all strategic types. Evidence was found of the endogenous emergence of a similarity measure of games based on the number and types of Nash equilibria, and of heuristics that have been found effective in describing human behavior in experimental one-shot games. The neural network agents were found to approximate experimental human behavior very well across various dimensions such as convergence to Nash equilibria, equilibrium selection, and adherence to principles of dominance and iterated dominance. This is corroborated by evidence from five studies of experimental one-shot games, because the Spearman correlation coefficients of the probability distribution over the neural networks’ and human subjects’ actions ranged from 0.49 to 0.89.

For mobile robots to communicate meaningfully about their spatial environment, they require personally constructed cognitive maps and social interactions to form languages with shared meanings. Geographic spatial concepts introduce particular problems for grounding—connecting a word to its referent in the world—because such concepts cannot be directly and solely based on sensory perceptions. In this article we investigate the grounding of geographic spatial concepts using mobile robots with cognitive maps, called Lingodroids. Languages were established through structured interactions between pairs of robots called where-are-we conversations. The robots used a novel method, termed the distributed lexicon table, to create flexible concepts. This method enabled words for locations, termed toponyms, to be grounded through experience. Their understanding of the meaning of words was demonstrated using go-to games in which the robots independently navigated to named locations. Studies in real and virtual reality worlds show that the system is effective at learning spatial language: robots learn words easily—in a single trial as children do—and the words and their meaning are sufficiently robust for use in real world tasks.

The agent-based model presented here builds on existing models, allowing for multiple partnerships, including those overlapping in time, to examine sexual partnerships, with the goal of hypothesis testing and guiding data collection. Within each model run, agents are assigned characteristics (including quality, aspiration, courtship duration, and ideal number of lifetime partners) and then search for partners; existing couples choose whether they should break up, remain dating, or become sexual partners. Model behavior was tested across a wide range of parameters and compared with empirical data. The model produces numbers of lifetime sexual partners, and partners in the last year, rates of concurrency, and relationship durations similar to nationally representative data from the United States; it also generates correlations in partners’ quality similar to those reported for marriage and dating partners. Model results highlight the importance of individual preferences, interactions between individuals, and contextual factors in sexual decision making.